{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e7baef65",
   "metadata": {},
   "source": [
    "饼图\n",
    "饼状图用来显示一个数据系列，具体来说，饼状图显示一个数据系列中各项目的占项目总和的百分比。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3b09d15c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams['axes.unicode_minus'] = False\n",
    "plt.rcParams['font.sans-serif'] = 'SimHei'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3e195b9a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = [10, 20, 30, 40]\n",
    "plt.figure(figsize=(5,3))\n",
    "plt.pie(x, autopct='%.1f%%')#autopct显示百分比，保留1位小数。后面加2个%才显示%\n",
    "#plt.savefig('images/5-18.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9b3a85d",
   "metadata": {},
   "source": [
    "Pandas读取excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ad1f1fc0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>省份</th>\n",
       "      <th>销量</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>广东</td>\n",
       "      <td>12932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>山东</td>\n",
       "      <td>9622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>湖北</td>\n",
       "      <td>9505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>江苏</td>\n",
       "      <td>7898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>浙江</td>\n",
       "      <td>7675</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   省份     销量\n",
       "0  广东  12932\n",
       "1  山东   9622\n",
       "2  湖北   9505\n",
       "3  江苏   7898\n",
       "4  浙江   7675"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel(r'D:\\MyFile\\WareHouse\\Gitee\\daily_code\\期末\\4\\plot.xlsx', \n",
    "                   sheet_name='pie1')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "84fdcf04",
   "metadata": {},
   "outputs": [],
   "source": [
    "citys, values = df.省份, df.销量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8e073352",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 饼图\n",
    "plt.figure(figsize=(3, 3))\n",
    "plt.pie(\n",
    "            x=values,   # 值\n",
    "            autopct='%.1f%%',  # 百分比\n",
    "            labels=citys,  # 标签\n",
    "            pctdistance=0.8,  # 百分比文字的位置。越大越偏离圆心\n",
    "            explode=[0, 0, 0, 0.1, 0, 0.1, 0, 0, 0, 0],  # 分裂效果\n",
    "            # 字体样式\n",
    "            textprops={'fontsize': 12, 'color': 'blue'},\n",
    "            shadow=True#阴影\n",
    "       )\n",
    "\n",
    "#plt.savefig('images/5-19.png')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
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